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We consider the challenge of AI value alignment with multiple individuals that have different reward functions and optimal policies in an underlying Markov decision process. We formalize this problem as one of policy aggregation, where the…

Artificial Intelligence · Computer Science 2024-11-07 Parand A. Alamdari , Soroush Ebadian , Ariel D. Procaccia

We study the problem of {\em impartial selection}, a topic that lies at the intersection of computational social choice and mechanism design. The goal is to select the most popular individual among a set of community members. The input can…

Computer Science and Game Theory · Computer Science 2021-02-19 Ioannis Caragiannis , George Christodoulou , Nicos Protopapas

We study a novel class of mechanism design problems in which the outcomes are constrained by the payments. This basic class of mechanism design problems captures many common economic situations, and yet it has not been studied, to our…

Computer Science and Game Theory · Computer Science 2013-12-02 Yaron Singer

We consider the problem of fairly allocating indivisible public goods. We model the public goods as elements with feasibility constraints on what subsets of elements can be chosen, and assume that agents have additive utilities across…

Computer Science and Game Theory · Computer Science 2018-05-10 Brandon Fain , Kamesh Munagala , Nisarg Shah

In this survey, we review the literature investigating participatory budgeting as a social choice problem. Participatory Budgeting (PB) is a democratic process in which citizens are asked to vote on how to allocate a given amount of public…

Computer Science and Game Theory · Computer Science 2025-03-14 Simon Rey , Felicia Schmidt , Jan Maly

We consider the problem of belief aggregation: given a group of individual agents with probabilistic beliefs over a set of uncertain events, formulate a sensible consensus or aggregate probability distribution over these events. Researchers…

Artificial Intelligence · Computer Science 2013-02-08 David M. Pennock , Michael P. Wellman

Behavioural economists have shown that people are often averse to inequality and will make choices to avoid unequal outcomes. In this paper, we consider how to allocate indivisible goods fairly so as to minimize inequality. We consider how…

Computer Science and Game Theory · Computer Science 2018-10-15 Martin Aleksandrov , Cunjing Ge , Toby Walsh

We consider the problem of designing auctions which maximize consumer surplus (i.e., the social welfare minus the payments charged to the buyers). In the consumer surplus maximization problem, a seller with a set of goods faces a set of…

Computer Science and Game Theory · Computer Science 2025-03-18 Tomer Ezra , Daniel Schoepflin , Ariel Shaulker

When making a decision as a group, there are two primary paradigms: aggregating preferences (e.g. voting, mechanism design) and aggregating information (e.g. discussion, consulting, forecasting). Almost all formally-studied group…

Computer Science and Game Theory · Computer Science 2025-03-03 Mary Monroe , Bo Waggoner

In approval-based multiwinner voting, voters express approval preferences over a set of candidates, and the goal is to return a winning committee. This model captures a broad range of subset selection problems under preferences. Prior work…

Computer Science and Game Theory · Computer Science 2026-04-28 Niclas Boehmer , Luca Kreisel , Jannik Peters

We revisit the classic problem of fair division from a mechanism design perspective, using {\em Proportional Fairness} as a benchmark. In particular, we aim to allocate a collection of divisible items to a set of agents while incentivizing…

Computer Science and Game Theory · Computer Science 2014-02-26 Richard Cole , Vasilis Gkatzelis , Gagan Goel

Public funding processes demand fairness, learning, and outcomes that participants can understand. We introduce Komitee Equal Shares, a priceable virtual-budget allocation framework that integrates two signals: in voter mode, participants…

Human-Computer Interaction · Computer Science 2025-10-03 Joshua C. Yang , Noemi Scheurer

In the committee voting setting, a subset of $k$ alternatives is selected based on the preferences of voters. In this paper, our goal is to efficiently compute $\textit{ex-ante}$ fair probability distributions over committees. We introduce…

Computer Science and Game Theory · Computer Science 2024-12-30 Mashbat Suzuki , Jeremy Vollen

This paper focuses on the coordination of a large population of dynamic agents with private information over multiple periods. Each agent maximizes the individual utility, while the coordinator determines the market rule to achieve group…

Systems and Control · Computer Science 2015-10-05 Sen Li , Wei Zhang

We study incentive compatible mechanisms for Combinatorial Auctions where the bidders have submodular (or XOS) valuations and are budget-constrained. Our objective is to maximize the \emph{liquid welfare}, a notion of efficiency for…

Computer Science and Game Theory · Computer Science 2018-12-14 Dimitris Fotakis , Kyriakos Lotidis , Chara Podimata

In many real-world situations, data is distributed across multiple self-interested agents. These agents can collaborate to build a machine learning model based on data from multiple agents, potentially reducing the error each experiences.…

Computers and Society · Computer Science 2023-02-28 Kate Donahue , Jon Kleinberg

In fair division, equitability dictates that each participant receives the same level of utility. In this work, we study equitable allocations of indivisible goods among agents with additive valuations. While prior work has studied…

Computer Science and Game Theory · Computer Science 2019-05-28 Rupert Freeman , Sujoy Sikdar , Rohit Vaish , Lirong Xia

Incentives are key to the success of crowdsourcing which heavily depends on the level of user participation. This paper designs an incentive mechanism to motivate a heterogeneous crowd of users to actively participate in crowdsourcing…

Multiagent Systems · Computer Science 2018-12-13 Tie Luo , Salil S. Kanhere , Sajal K. Das , Hwee-Pink Tan

Partially Observable Markov Decision Processes (POMDPs) provide an efficient way to model real-world sequential decision making processes. Motivated by the problem of maintenance and inspection of a group of infrastructure components with…

Optimization and Control · Mathematics 2024-08-15 Manav Vora , Pranay Thangeda , Michael N. Grussing , Melkior Ornik

We study a problem where a group of agents has to decide how a joint reward should be shared among them. We focus on settings where the share that each agent receives depends on the subjective opinions of its peers concerning that agent's…

Computer Science and Game Theory · Computer Science 2013-05-23 Arthur Carvalho , Kate Larson
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